The deal values Manus at between $2 billion and $3 billion, although Meta has chosen not to disclose financial terms. Manus, now based in Singapore, did not respond to requests for comment at the time of writing.

The acquisition gives Meta full control of Manus’s technology, which it plans to operate, sell and embed across its consumer and business products, including Meta AI. 

This will help to secure what many in the industry now see as the most valuable layer in AI development, the execution layer, where software agents go beyond conversation to carry out complex tasks on their own.

Manus rose quickly into the global spotlight earlier this year after releasing what it described as a general AI agent. Unlike standard chatbots, the system was designed to make decisions and complete tasks with minimal prompting. 

The product went viral on X and was soon compared to DeepResearch, a benchmark tool in the sector. The company has claimed its agent outperforms that system, helping to drive both attention and controversy.

Behind the attention was rapid commercial growth. Manus became the fastest startup to cross $100 million in annual recurring revenue, reaching a $125 million run rate in under eight months. 

In 2025 alone, its systems processed 147 trillion tokens and powered around 80 million virtual computers, figures that point to unusual scale for a company so young. That pace made Manus one of the most talked-about AI agent startups globally.

Meta’s interest shows a change in strategy. While the company has spent years building open-source foundation models such as Llama, this deal reveals a goal to own proprietary systems that sit on top of those models and actually do the work. 

Autonomous agents that can research, write code and analyse data are now the next battleground, and competition is increasing fast.

The acquisition comes after a year of heavy spending by Meta, including its investment in Scale AI, a deal that valued the data-labelling firm at $29 billion. 

Competitors are not standing still. Microsoft is expanding Copilot, Google is pushing Gemini, and OpenAI is developing DeepResearch.

Manus’s background also adds a geopolitical edge to the deal. Founded in China and backed by its parent company, Beijing Butterfly Effect Technology, the startup was once described as China’s next DeepSeek. 

It later relocated to Singapore, joining a growing number of Chinese tech firms seeking to reduce exposure to Sino-US tensions. Singapore’s neutral stance and trade-friendly policies have made it a preferred base for global expansion.

Beijing had shown interest in supporting Manus, and the company maintains a strategic partnership with Alibaba to collaborate on AI models. 

Meta’s acquisition changes ownership firmly to a U.S. technology giant, a development that is likely to be closely watched in both Washington and Beijing.

This rapid growth is driven by the widespread adoption of AI technologies by businesses worldwide. From chatbots in customer service to advanced data analytics, companies are increasingly using AI to boost efficiency, improve decision-making, and foster innovation, contributing to market expansion.

Governments globally are investing heavily in AI to improve public services, modernize infrastructure, and support digital transformation. 

This public sector investment complements the efforts of private enterprises, which are also pouring resources into AI research and development to maintain their competitive edge.

As a result, industries such as defense, healthcare, and smart cities benefit from the accelerated development and deployment of autonomous AI systems.

The market is categorized into on-premises and cloud deployment models. In 2024, cloud-based solutions accounted for more than 65% of the market share and are expected to exceed USD 90 billion by 2034.

Cloud deployment allows businesses to efficiently manage large data sets and scale operations as required. 

This is particularly valuable in sectors like healthcare, finance, and retail, where rapid AI adoption is crucial. 

By utilizing the cloud, companies can avoid significant upfront investments in IT infrastructure, enabling easier and more cost-effective deployment of AI solutions.

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While workers feel most comfortable when AI and humans work together, they are beginning to trust AI to complete time-saving tasks autonomously, like writing code, uncovering data insights, and drafting written communications.

Workers aren’t delegating everything to AI just yet.

According to the research, today’s workers prefer that humans oversee tasks like onboarding, training, and data security. But this likely won’t last for long.

The data also suggests that investing in knowledge and education builds trust in an autonomous AI future.

As technology advances, people are getting a glimpse into a future in which AI can operate entirely on its own.

The Salesforce research, which surveyed nearly 6,000 people around the world, revealed that workers are excited about an AI-powered future.

Additionally, they also stressed the importance of a human touch as they build trust, knowledge, and experience with AI tools.

Global workers, especially leaders, believe in an autonomous future and are already offloading tasks to AI

Workers today already trust AI to do roughly 43% of their work tasks, indicating a shift among workers to offload tasks to AI.

Leaders trust AI to do more of their work than employees do — leaders trust AI to do 51% of their work, while rank-and-file workers trust AI to do 40%.

• 77% of global workers will eventually trust AI to operate autonomously. This number includes:
  • 10% of global workers trust AI to operate autonomously today.
  • 26% of global workers will trust AI to operate autonomously in less than three years.
  • 41% of global workers will trust AI to operate autonomously in three or more years.

While workers prefer AI-human collaboration, they’re starting to trust AI to handle certain tasks alone

• Today, 54% of global workers trust humans and AI to do most work tasks together.
• When asked if these workers trusted AI to do any of these same tasks autonomously, the answer, for a small group, was some. Tasks they felt comfortable offloading to autonomous AI included:
  • 15% trust AI to write code autonomously.
  • 13% trust AI to uncover data insights on its own.
  • 12% trust AI to develop internal and external communications without a human.
  • 12% trust autonomous AI to act as their personal assistant.
• Other tasks, according to respondents, require having a human involved right now. Global workers are most likely to trust humans alone to do the following:
  • 47% trust humans alone to be inclusive.
  • 46% trust humans alone to onboard and train employees.
  • 40% trust humans alone to keep data safe.

Human involvement and enablement can pave the way to an autonomous AI future

• Human involvement is needed to build trust in AI.
  • 63% of global workers say more human involvement would build their trust in AI.
• Concerns about AI may come from a lack of understanding. Fifty-four percent of global workers say they do not know how AI is implemented or governed in their workplace.
  • Workers who are knowledgeable about how AI is implemented and governed in their workplace are five times more likely to say they will trust AI to operate autonomously within the next two years than those who are not knowledgeable.

The AI Knowledge Gender Gap: Males are 94% more likely to say they are knowledgeable about how AI is implemented and governed in their workplace compared to females.

Training may be another key to trusted autonomy

62% of workers say more skill-building and training opportunities would build their trust in AI.

“Workers are excited about an AI-powered future and the research shows us that human engagement can help us get there. By empowering humans at the helm of today’s AI systems, we can build trust and drive adoption – enabling workers to unlock all that AI has to offer,” says Linda Saunders, Salesforce Director, Solutions Engineering Africa.